package com.atguigu.state;

import com.atguigu.bean.WaterSensor;
import com.atguigu.functions.WaterSensorMapFunction;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.common.state.MapState;
import org.apache.flink.api.common.state.MapStateDescriptor;
import org.apache.flink.api.common.state.ReducingState;
import org.apache.flink.api.common.state.ReducingStateDescriptor;
import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.configuration.Configuration;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.KeyedProcessFunction;
import org.apache.flink.util.Collector;

import java.time.Duration;
import java.util.Map;

/**
 * TODO 计算每种传感器的水位和
 *
 * @author cjp
 * @version 1.0
 */
public class KeyedReducingStateDemo {
  public static void main(String[] args) throws Exception {
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    env.setParallelism(1);
    
    
    SingleOutputStreamOperator<WaterSensor> sensorDS = env
        .socketTextStream("hadoop102", 7777)
        .map(new WaterSensorMapFunction())
        .assignTimestampsAndWatermarks(
            WatermarkStrategy
                .<WaterSensor>forBoundedOutOfOrderness(Duration.ofSeconds(3))
                .withTimestampAssigner((element, ts) -> element.getTs() * 1000L)
        );
    
    sensorDS.keyBy(r -> r.getId())
        .process(
            new KeyedProcessFunction<String, WaterSensor, String>() {
              
              ReducingState<Integer> vcSumReducingState;
              
              @Override
              public void open(Configuration parameters) throws Exception {
                super.open(parameters);
                vcSumReducingState = getRuntimeContext()
                    .getReducingState(
                        new ReducingStateDescriptor<Integer>(
                            "vcSumReducingState",
                            new ReduceFunction<Integer>() {
                              @Override
                              public Integer reduce(Integer value1, Integer value2) throws Exception {
                                return value1 + value2;
                              }
                            },
                            Types.INT
                        )
                    );
              }
              
              @Override
              public void processElement(WaterSensor value, Context ctx, Collector<String> out) throws Exception {
                // 来一条数据，添加到 reducing状态里
                vcSumReducingState.add(value.getVc());
                Integer vcSum = vcSumReducingState.get();
                out.collect("传感器id为" + value.getId() + ",水位值总和=" + vcSum);


//                                vcSumReducingState.get();   // 对本组的Reducing状态，获取结果
//                                vcSumReducingState.add();   // 对本组的Reducing状态，添加数据
//                                vcSumReducingState.clear(); // 对本组的Reducing状态，清空数据
              }
            }
        )
        .print();
    
    env.execute();
  }
}
